The information provided in this section is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
The present disclosure relates to image classification and more particularly to a convolutional processing image classification system that can resize a received image and modify a feature map.
Image processing typically includes the processing of pixel values of an image. The pixels can be arranged as an array that represent an image size. The pixel values are generated by an image capture device, such as a camera, that may be a still image or a sequence of still images.
Neural networks can be used in image classification, object detection, and other recognition tasks. A convolutional neural network is a type of deep, feed-forward neural network that is used to analyze multiple images. Convolutional neural networks typically include one or more convolutional layers, pooling layers, fully connected layers, and normalization layers.